Composites

Composites combine multiple hypervectors into higher-level structures. Each composite type uses a different combination strategy, preserving different kinds of relationships between its members.

All composites follows the same contract (interface in Go and traits in Rust) and can be nested — a Set can contain Sparkles, Knots, or even other Sets.

Set

An unordered collection of concepts.

$$S=S_{marker}\otimes (\sum _{i,\oplus }{M}_i)$$

where $S_{marker}$ is a special marker to distinguish a set from its individual members.

This mark is tuned for the domain, so that it will be shared among all sets within the same domain.

Use when: you need to represent “these things together” without order.

Check out code snippets from the API reference.

Sequence

An ordered collection.

$$S=S_{marker}\otimes (\sum _{i,\oplus }{M}_i\otimes S_{step}^i)$$

where $S_{step}$ is a generic hypervector for positional encoding.

$S_{marker}$ is a special marker to distinguish a sequence from its individual members. This mark is tuned for the domain, so that it will be shared among all sequences within the same domain.

Use when: order matters (e.g., words in a sentence, events in time).

Check out code snippets from the API reference.

Octopus

A key-value structure. Each key (a string) is converted to a Sparkle and bound with its corresponding value before bundling.

$$S=\sum _{i,\oplus }{K}_i\otimes V_i$$

Use when: you need to represent structured records with named attributes.

Check out code snippets from the API reference.

Knot

The result of binding (multiplicative composition) of hypervectors.

$$S=\prod _{i,\otimes }{M}_i$$

Binding is reversible: given a Knot of A and B, you can recover A by releasing B (binding with B’s inverse).

Use when: you need a reversible association between concepts.

Check out code snippets from the API reference.

Parcel

The result of bundling (additive composition).

$$S=\sum _{i,\oplus }{M}_i$$

Unlike direct bundling, Parcel keeps tracking of its members for serialization and introspection.

Use when: you need a superposition of concepts, with optional weights.

Check out code snippets from the API reference.

Summary